Six-minute walk test distance at time of hospital discharge is strongly and independently associated with all-cause mortality following cardiac surgery.

Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
30 Jan 2024
Historique:
received: 18 07 2023
accepted: 21 01 2024
medline: 31 1 2024
pubmed: 31 1 2024
entrez: 30 1 2024
Statut: epublish

Résumé

We investigated the impact of distance covered in the six-minute walk test (6mWT) before being discharged from the hospital after cardiac surgery on the risk of all-cause mortality. Our study included 1127 patients who underwent cardiac surgery and then took part in a standardised physiotherapist-supervised inpatient rehabilitation programme during 2007-2017. The percentage of the predicted 6mWT distance, and the lower limit of normal distance was calculated based on individual patients' age, sex, and body mass index. We used Cox regression with adjustment for confounders to determine multivariable-adjusted hazard ratios (HRs) for mortality. Over a median follow-up period of 6.4 (IQR: 3.5-9.2) years, 15% (n = 169) patients died. We observed a strong and independent inverse association between 6mWT distance and mortality, with every 10 m increase in distance associated to a 4% reduction in mortality (HR: 0.96, 95% CI 0.94-0.98, P < 0.001). Those in the top tertile for predicted 6mWT performance had a 49% reduced risk of mortality (HR: 0.51, 95% CI 0.33-0.79) compared to those in the bottom tertile. Patients who met or exceeded the minimum normal 6mWT distance had 36% lower mortality risk (HR: 0.64, 95% CI 0.45-0.92) compared to those who did not meet this benchmark. Subgroup analysis showed that combined CABG and valve surgery patients walked less in the 6mWT compared to those undergoing isolated CABG or valve surgeries, with a significant association between 6mWT and mortality observed in the isolated procedure groups only. In conclusion, the longer the distance covered in the 6mWT before leaving the hospital, the lower the risk of mortality.

Identifiants

DOI: 10.1038/s41598-024-52601-7 PMID: 38291336
pubmed: 38291336
doi: 10.1038/s41598-024-52601-7
pii: 10.1038/s41598-024-52601-7
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

2493

Subventions

Organisme : National Health and Medical Research Council
ID : APP11447430

Informations de copyright

© 2024. The Author(s).

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Auteurs

Md Shajedur Rahman Shawon (MSR)

Centre for Big Data Research in Health, University of New South Wales, Sydney, Australia.

Benjumin Hsu (B)

Centre for Big Data Research in Health, University of New South Wales, Sydney, Australia.

Richard Chard (R)

Department of Cardiothoracic Surgery, Westmead Private Hospital, Westmead, NSW, Australia.
Faculty of Medicine, University of Sydney, Sydney, NSW, Australia.

Ian A Nicholson (IA)

Department of Cardiothoracic Surgery, Westmead Private Hospital, Westmead, NSW, Australia.
Faculty of Medicine, University of Sydney, Sydney, NSW, Australia.

Victoria L Elias (VL)

Westmead Private Hospital Physiotherapy Services, Westmead Private Hospital Sydney, Westmead, NSW, Australia.

Lauren K Nicola (LK)

Westmead Private Hospital Physiotherapy Services, Westmead Private Hospital Sydney, Westmead, NSW, Australia.

Corrina R Moore (CR)

Westmead Private Hospital Physiotherapy Services, Westmead Private Hospital Sydney, Westmead, NSW, Australia.

Andrew D Hirschhorn (AD)

MQ Health, Faculty of Medicine, Health and Human Sciences, Macquarie University, Maquarie Park, NSW, Australia.

Louisa R Jorm (LR)

Centre for Big Data Research in Health, University of New South Wales, Sydney, Australia.

Sean F Mungovan (SF)

Westmead Private Hospital Physiotherapy Services, Westmead Private Hospital Sydney, Westmead, NSW, Australia. sean.mungovan@crinstitute.com.au.
The Clinical Research Institute, Westmead, NSW, Australia. sean.mungovan@crinstitute.com.au.
Department of Professions, Faculty of Health, Arts and Design, Swinburne University of Technology, Hawthorn, VIC, Australia. sean.mungovan@crinstitute.com.au.

Classifications MeSH